At Airbnb, we need to ensure every area of the business has trustworthy data to fuel insight and innovation. Understanding the business need, securing the right data sources, designing usable data models, and building robust & dependable data pipelines are essential skills to meet this goal.

We are currently hiring for the following teams:

Host Success team: Host Success is where business partners, sales leads, product managers, data scientists, data engineers, machine learning engineers and backend engineers all come together to help Hosts be more successful on Airbnb through data powered recommendations, or new programs. This includes helping Hosts optimize their pricing and availability, providing insights for Hosts to better understand their performance, and leverage all the Host tooling to maximize the appeal for their listings to guests.

Guest Data Engineering team: Understanding how guests and hosts use our products allows us to give them the best possible booking experience. Airbnb competes in the marketplace by transforming data into intelligence. Given the scale of our operation (millions of bookings / month), we must leverage data to understand how successful our customers are at completing the tasks required to make and modify bookings. We must also ensure teams are consistently feeding that information back into our product to improve the user experience. The Guest Data team leverages (or builds) the best tools, frameworks and data assets to make it incredibly easy to derive valuable product insights about our core booking funnel.

The Difference You Will Make:

Host Success team: You will partner with the sales and product teams to build data models, to produce actionable that’s integrated with our sales platform to enable hundreds of sales people to more effectively engage with Hosts and help them be more successful on our platform. You will also collaborate with data scientists and ML engineers to iterate on the prioritization of recommendations, track conversion, and report on the business impact of this effort to iteratively improve on the quality and impact of our recommendations.

Guest Data Engineering team: As part of the Guest Data Engineering team, you will closely work with cross-functional partners in Product, Analytics Engineering, Data Science, and ML/AI to produce high quality data tools and assets, ensure data governance, and empower partners to easily find, understand and use data. In this role, you will play a pivotal role collaborating with the SEO team to directly impact people’s ability to discover Airbnb for their next stay. SEO operates at an incredible scale, promoting hundreds of thousands of destinations and experiences spanning a broad range of languages and international locales. Data forms the foundation of SEO systems and platforms. You will collaborate with a talented cross functional team to set and execute on our data strategy, to directly influence our ability to understand how guests and search engines interact with Airbnb. You will solve compelling technical and data modeling challenges to directly influence one of the fastest-growing free and owned marketing channels.

A Typical Day:

  • Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
  • Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
  • Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
  • Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
  • Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
  • Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

  • 5-9+ years of relevant industry experience with a BS/Masters, or 2+ years with a PhD
  • Experience with distributed processing technologies and frameworks, such as Hadoop, Spark, Kafka, and distributed storage systems (e.g., HDFS, S3)
  • Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
  • Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
  • Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
  • Excellent written and verbal communication skills

Your Location:

This position is US – Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. Airbnb, Inc. can employ in states where we have registered entities. Currently, employees can not be located in: Alaska, Indiana, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin, Alabama, Mississippi, Oklahoma, Delaware or Rhode Island. As this list is continuously evolving and being updated, please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the best and brightest people from the broadest talent pool possible. We believe a diversity of ideas foster innovation and engagement, allow us to attract the best people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. If you need assistance or a reasonable accommodation during the application and recruiting process, please contact us at: [email protected].

How We’ll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range
$185,000$221,000 USD